About

My work bridges Machine Learning, Network Science, and Data Science, with a strong emphasis on human-centric, trustworthy AI. I design and deploy methodologies that advance explainability, fairness, and transparency, translating research into accountable systems aligned with societal values.

I lead industrial collaborations bringing generative AI to high-stakes domains such as legal document analysis and anti-financial-crime compliance, pairing technical innovation with regulatory alignment. I also serve as PI of the EU-funded PRE-ACT consortium—running a Phase III trial on AI-assisted breast radiotherapy decisions—building bias-aware evaluation pipelines and practical guidelines for Fair, Transparent & Ethical AI.

Over 15+ years I've contributed to both foundational research and scalable systems in complex socio-technical settings, including real-time data pipelines and graph-based learning for behavior modeling and risk detection. My research spans graph neural networks, XAI, and LLM-powered document analysis (RAG), with publications at NeurIPS, KDD, TKDE, TMLR, and WWW.

Experience

Principal Research Scientist
Intesa Sanpaolo — AI Research
Jan 2026 – Present · Turin, Italy
Principal Researcher & Team Lead — Responsible AI
CENTAI Institute
May 2022 – Jan 2026 · Turin, Italy
  • Led the Responsible AI team, designing methodologies and tools that promote explainability, fairness, and transparency in AI systems
  • Directed industry collaborations on GenAI for legal document analysis and financial crime compliance
  • Mentored interdisciplinary teams and supervised PhD/MSc research in Responsible AI
Adjunct Professor (Professore a Contratto)
Università degli Studi di Torino — Physics Department
2014 – 2025 · Turin, Italy
  • Course on Data Mining, Statistical Modeling and Machine Learning for the MSc in Physics of Complex Systems
Senior Research Scientist
ISI Foundation
Feb 2013 – Apr 2022 · Turin, Italy
  • Built data analysis tools and ML models to study human behavior, epidemic spreading, and digital trace analytics
  • Built real-time interaction monitoring systems with wearable sensors (SocioPatterns)
  • Co-authored open-source data visualization tools (datainterfaces.org, ebolatracking.org)
  • Led collaborations in fairness-aware analytics, public health modeling, and health insurance risk
Post-doctoral Researcher
ISI Foundation
Jan 2012 – Jan 2013 · Turin, Italy
Fellow
Insight Data Science
2012 · Palo Alto, CA
  • Created a real-time hot-topic tracker on Twitter using graph-based user expansion (Python + D3.js)
PhD Researcher & Lecturer
University of Turin
2009 – 2011 · Turin, Italy
Software Architect
Xeffe / ValueTeam
2008 – 2011 · Turin, Italy
  • Led architectural design for banking platforms (Java, Oracle)
  • Optimized data pipelines and transaction throughput across hybrid systems
Education
Ph.D. Computer Science
University of Turin, Italy · 2009–2011
M.Sc. Computer Science
Federal University of Rio Grande do Sul (UFRGS), Brazil · 2004–2006
B.Sc. Computer Science
Federal University of Rio Grande do Sul (UFRGS), Brazil · 1999–2003

Publications

2025
A. Ferrara, F. Cozzi, A. Perotti, A. Panisson, F. Bonchi. Size-adaptive Hypothesis Testing for Fairness. Neural Information Processing Systems (NeurIPS 2025). NeurIPS
F. Cozzi, M. Pangallo, A. Perotti, A. Panisson, C. Monti. Learning Individual Behavior in Agent-Based Models with Graph Diffusion Networks. Neural Information Processing Systems (NeurIPS 2025). NeurIPS
F. Bonchi, C. Gentile, F.P. Nerini, A. Panisson, F. Vitale. Fast and Effective GNN Training through Sequences of Random Path Graphs. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025). KDD
E. Pastor, E. Poeta, A. Panisson, A. Perotti, G. Ciravegna. Beyond Input Attribution: A Hands-On Tutorial to Concept-Based Explainable AI and Mechanistic Interpretability. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025). KDD
S. Piaggesi, A. Panisson, M. Khosla. Disentangled and Self-Explainable Node Representation Learning. Transactions on Machine Learning Research (TMLR 2025).
2024
A. Perotti, C. Borile, A. Miola, F. P. Nerini, P. Baracco, A. Panisson. Explainability, Quantified: Benchmarking XAI Techniques. In: Explainable Artificial Intelligence. xAI 2024. Communications in Computer and Information Science, vol 2153. DOI
S. Piaggesi, M. Khosla, A. Panisson and A. Anand. DINE: Dimensional Interpretability of Node Embeddings. In IEEE Transactions on Knowledge and Data Engineering. (2024) DOI
C. Monti, P. Bajardi, F. Bonchi, A. Panisson, A. Perotti. A True-to-the-model Axiomatic Benchmark for Graph-based Explainers. Transactions on Machine Learning Research. (2024) PDF
F. P. Nerini, P. Bajardi, A. Panisson. Value is in the Eye of the Beholder: A Framework for an Equitable Graph Data Evaluation. In Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT '24). FAccT DOI
S. Pasteris, F. Vitale, M. Herbster, C. Gentile, A. Panisson. Adversarial Online Collaborative Filtering. In Proceedings of the 35th International Conference on Algorithmic Learning Theory (ALT 2024), PMLR 237:945-971.
2023
A. Battiston, L. Napoli, P. Bajardi, A. Panisson, A. Perotti, M. Szell, R. Schifanella. Revealing the determinants of gender inequality in urban cycling with large-scale data. EPJ Data Science. 12(1): 9.
C. Borile, A. Perotti, A. Panisson. Evaluating Link Prediction Explanations for Graph Neural Networks. In: Explainable Artificial Intelligence. xAI 2023. Communications in Computer and Information Science, vol 1902.
F. Dibitonto, F. Garcea, A. Panisson, A. Perotti, L. Morra. HOLMES: HOLonym-MEronym Based Semantic Inspection for Convolutional Image Classifiers. In: Explainable Artificial Intelligence. xAI 2023. Communications in Computer and Information Science, vol 1902.
A. Perotti, S. Bertolotto, E. Pastor, A. Panisson. Beyond One-Hot-Encoding: Injecting Semantics to Drive Image Classifiers. In: Explainable Artificial Intelligence. xAI 2023. Communications in Computer and Information Science, vol 1902, 525–548.
A. Perotti, P. Bajardi, F. Bonchi, A. Panisson. Explaining Identity-aware Graph Classifiers through the Language of Motifs. Proceedings of the 2023 International Joint Conference on Neural Networks (IJCNN).
J. Lenti, Y. Mejova, K. Kalimeri, A. Panisson, D. Paolotti, M. Tizzani, M. Starnini. Global Misinformation Spillovers in the Vaccination Debate Before and During the COVID-19 Pandemic: Multilingual Twitter Study. JMIR Infodemiology. 2023 May 24;3:e44714.
A. Capozzi, G. D. F. Morales, Y. Mejova, C. Monti, and A. Panisson. The Thin Ideology of Populist Advertising on Facebook during the 2019 EU Elections. In Proceedings of the ACM Web Conference 2023 (WWW '23). WWW
2022
S. Piaggesi, A. Panisson, & G. Petri. Effective Higher-order Link Prediction and Reconstruction from Simplicial Complex Embeddings. In Learning on Graphs Conference (pp. 55-1). PMLR.
S. Piaggesi & A. Panisson. Time-varying graph representation learning via higher-order skip-gram with negative sampling. EPJ Data Science, 11(1), 33.
C. Rollo, G. De Francisci Morales, C. Monti, & A. Panisson. Communities, Gateways, and Bridges: Measuring Attention Flow in the Reddit Political Sphere. In Social Informatics: 13th International Conference, SocInfo 2022, Proceedings (pp. 3–19).
G. Crupi, Y. Mejova, M. Tizzani, D. Paolotti, and A. Panisson. Echoes through time: Evolution of the Italian COVID-19 vaccination debate. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 16, pp. 102–113). ICWSM
2021
S. Giurgola, S. Piaggesi, M. Karsai, Y. Mejova, A. Panisson & M. Tizzoni. Mapping urban socioeconomic inequalities in developing countries through Facebook advertising data. Frontiers in Big Data, 5.
C. Panigutti, A. Perotti, A. Panisson, P. Bajardi, & D. Pedreschi. FairLens: Auditing black-box clinical decision support systems. Information Processing & Management, 58(5), 102657.
E. G. Amparore, F. Cinus, C. Maestri, L. Petrocchi, D. Polinelli, F. Scarpa, A. Perotti, A. Panisson, P. Bajardi. Forecast of Distributed Energy Generation and Consumption in a Partially Observable Electrical Grid: A Machine Learning Approach. 2021 IEEE Madrid PowerTech, pp. 1–6.
M. Starnini, C. E. Tsourakakis, M. Zamanipour, A. Panisson, W. Allasia, M. Fornasiero, L. Li Puma, V. Ricci, S. Ronchiadin, A. Ugrinoska, M. Varetto, D. Moncalvo. Smurf-Based Anti-money Laundering in Time-Evolving Transaction Networks. Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, Cham.
A. Capozzi, G. De Francisci Morales, Y. Mejova, C. Monti, A. Panisson, & D. Paolotti. Clandestino or Rifugiato? Anti-immigration Facebook Ad Targeting in Italy. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1–15). CHI
F. Poletto, Y. Zhang, A. Panisson, Y. Mejova, D. Paolotti, & S. Ponserre. Developing Annotated Resources for Internal Displacement Monitoring. In Companion Proceedings of the Web Conference 2021 (pp. 136–144).
2020
A. Capozzi, G. De Francisci Morales, Y. Mejova, C. Monti, A. Panisson, & D. Paolotti. Facebook Ads: Politics of Migration in Italy. In International Conference on Social Informatics (pp. 43–57).
N. Gozzi, M. Tizzani, M. Starnini, F. Ciulla, D. Paolotti, A. Panisson, & N. Perra. Collective response to media coverage of the COVID-19 pandemic on Reddit and Wikipedia: mixed-methods analysis. Journal of Medical Internet Research, 22(10), e21597.
F. Cinus, F. Bonchi, C. Monti, A. Panisson. Generating Realistic Interest-Driven Information Cascades. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 107–118). ICWSM
M. Tizzoni, A. Panisson, D. Paolotti, C. Cattuto. The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic. PLoS Computational Biology 16(3), e1007633.
B. Edizel, F. Bonchi, S. Hajian, A. Panisson, T. Tassa. FaiRecSys: Mitigating algorithmic bias in recommender systems. International Journal of Data Science and Analytics, 9(2), 197–213.
2019
D. Balsamo, P. Bajardi, A. Panisson. Firsthand Opiates Abuse on Social Media: Monitoring Geospatial Patterns of Interest Through a Digital Cohort. In Proceedings of the 2019 World Wide Web Conference. WWW
S. Piaggesi, L. Gauvin, M. Tizzoni, C. Cattuto, N. Adler, S. Verhulst, A. Panisson. Predicting City Poverty Using Satellite Imagery. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 90–96).
B. Gobbo, D. Balsamo, M. Mauri, P. Bajardi, A. Panisson, P. Ciuccarelli. Topic Tomographies (TopTom): a visual approach to distill information from media streams. In Computer Graphics Forum (Vol. 38, No. 3, pp. 609–621).
L. Ozella, L. Gauvin, L. Carenzo, M. Quaggiotto, P.L. Ingrassia, M. Tizzoni, A. Panisson, D. Colombo, A. Sapienza, K. Kalimeri, F. Della Corte, C. Cattuto. Wearable proximity sensors for monitoring a mass casualty incident exercise: a feasibility study. Journal of Medical Internet Research 21(4), e12251. PDF
2018
M. Tizzoni, A. Panisson, D. Paolotti, C. Cattuto. The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic. bioRxiv, 346411. DOI
2016
M.C. Kiti, M. Tizzoni, T.M. Kinyanjui, D.C. Koech, P.K. Munywoki, M. Meriac, L. Cappa, A. Panisson, A. Barrat, C. Cattuto, D.J. Nokes. Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors. EPJ Data Science 5(1), 21. DOI
M.G. Beiró, A. Panisson, M. Tizzoni, C. Cattuto. Predicting human mobility through the assimilation of social media traces into mobility models. EPJ Data Science 5:30. DOI
2015
A. Sapienza, A. Panisson, J. Wu, L. Gauvin, C. Cattuto. Detecting anomalies in time-varying networks using tensor decomposition. Proceedings of the 5th IEEE ICDM Workshop on Data Mining in Networks. DOI
A. Sapienza, A. Panisson, J. Wu, L. Gauvin, C. Cattuto. Anomaly Detection in Temporal Graph Data: An Iterative Tensor Decomposition and Masking Approach. 1st International Workshop on Advanced Analytics and Learning on Temporal Data (AALTD 2015). PDF
P. Bajardi, M. Delfino, A. Panisson, G. Petri, M. Tizzoni. Unveiling patterns of international communities in a global city using mobile phone data. EPJ Data Science 4, no. 1: 1–17. DOI
L. Gauvin, A. Panisson, A. Barrat, C. Cattuto. Revealing latent factors of temporal networks for mesoscale intervention in epidemic spread. arXiv preprint arXiv:1501.02758. arXiv:1501.02758
2014
A. Panisson, L. Gauvin, M. Quaggiotto, C. Cattuto. Mining Concurrent Topical Activity in Microblog Streams. Proceedings of the 4th Workshop on Making Sense of Microposts, co-located with WWW 2014, Seoul, Korea. WWW Best Paper arXiv:1403.1403
L. Gauvin, A. Panisson, C. Cattuto. Detecting the community structure and activity patterns of temporal networks: a non-negative tensor factorization approach. PLOS ONE 9.1: e86028. DOI
2013
L. Gauvin, A. Panisson, C. Cattuto, A. Barrat. Activity clocks: spreading dynamics on temporal networks of human contact. Scientific Reports, v. 3, p. 3099. DOI
C. Cattuto, M. Quaggiotto, A. Panisson, A. Averbuch. Time-varying social networks in a graph database. First International Workshop on Graph Data Management Experiences and Systems (GRADES '13). ACM Press. DOI
A. Panisson, L. Gauvin, A. Barrat, C. Cattuto. Fingerprinting temporal networks of close-range human proximity. International Workshop on the Impact of Human Mobility in Pervasive Systems and Applications (PerMoby 2013), San Diego, CA. DOI
2012
A. Panisson, A. Barrat, C. Cattuto, G. Ruffo, R. Schifanella. On the Dynamics of Human Proximity for Data Diffusion in Ad-Hoc Networks. Ad Hoc Networks, Special Issue on Social-Based Routing in Mobile and Delay-Tolerant Networks, Volume 10, Issue 8, pp. 1532–1543. DOI arXiv
Melchiors, C., Mattjie, D.T., dos Santos, C.R.P., Panisson, A., Granville, L.Z., Tarouco, L.M.R. A P2P-Based Strongly Distributed Network Polling Solution. Advancements in Distributed Computing and Internet Technologies: Trends and Issues. IGI Global, pp. 289–313.
2011
A. Basso, M. Milanesio, A. Panisson, G. Ruffo. On Collaborative Filtering Techniques for Live TV and Radio Discovery and Recommendation. In Proceedings of the 12th International Conference on Electronic Commerce and Web Technologies (EC-Web 2011), Toulouse, France.
2010
A. Basso, M. Milanesio, A. Panisson. From Recordings to Recommendations: Suggesting Live Events in the DVR Context. In Proceedings of the International Workshop on the Practical Use of Recommender Systems, Algorithms and Technologies (RECSYS 2010), Barcelona, Spain.
A. Basso, M. Milanesio, A. Panisson. Social Aspects of Video Recording. In Proceedings of the Thirty Sixth Annual Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB10), Leicester, UK.
C. Melchiors, A.H. dos Santos, D. Mattjie, C.R. dos Santos, A. Panisson, L.Z. Granville, L.M. Tarouco. A network polling solution through a P2P-based distributed management environment. In Proceedings of the 2010 ACM Symposium on Applied Computing (SAC '10). ACM, New York, NY, 729–730.
2008
R. Schifanella, A. Panisson, C. Gena and G. Ruffo. MobHinter: Epidemic Collaborative Filtering and Self-Organization in Mobile Ad-Hoc Networks. 2nd ACM International Conference on Recommender Systems (RecSys 2008), Lausanne, Switzerland. ACM Press.
Marquezan, C.C., Panisson, A., Granville, L.Z., Nunzi, G., Brunner, M. Maintenance of Monitoring Systems Throughout Self-Healing Mechanisms. Proceedings of the 19th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management (DSOM 2008), Samos Island, Greece, pp. 176–188.
Panisson, A., Ruffo, G., and Schifanella, R. X-hinter: a framework for implementing social oriented recommender systems. In Proceedings of the 19th ACM Conference on Hypertext and Hypermedia (HT '08), Pittsburgh, PA. ACM, p. 235–236. PDF
2006
Panisson, A., Rosa, D.M., Melchiors, C., Granville, L.Z., Almeida, M.J.B., Tarouco, L.M.R. Designing the Architecture of P2P-Based Network Management Systems. IEEE Symposium on Computers and Communications (ISCC 2006), Pula-Cagliari, pp. 69–75. DOI
2005
Granville, L.Z., Rosa, D.M., Panisson, A., Melchiors, C., Almeida, M.J.B., Tarouco, L.M.R. Managing Computer Networks Using Peer-to-Peer Technologies. IEEE Communications Magazine, v. 43, n. 10, p. 62–68. PDF
Panisson, A., Almeida, M.J.B., Tarouco, L.M.R., Granville, L.Z. Implementação de um Algoritmo para Busca em Redes Peer-to-Peer. In: Brazilian Workshop on Peer-to-Peer Systems (WP2P-SBRC2005), Fortaleza. PDF
2004
Panisson, A., Vianna, R.L., Alves, R.S., Rochol, J. Segurança em Redes Ópticas: Tipos de Ataques e Métodos de Detecção. In: 2nd Regional School in Computer Networks (ERRC 2004), Canoas.
Theses
PhD thesis — University of Turin
Selective Information Dissemination for Mobile Computing PDF
Master thesis — UFRGS (Portuguese)
Load Distribution in a P2P-Based Network Management System PDF
Graduation thesis — UFRGS (Portuguese)
Implementação de um Algoritmo de Busca com Controle de Tráfego Distribuído e Adaptação de Topologia para Redes Peer-to-Peer Baseadas na Plataforma JXTA PDF ZIP

Teaching & Supervision

Teaching
  • Adjunct Professor, University of Turin (2013–2025): Course on Data Mining, Statistical Modeling and Machine Learning within the MSc in Physics of Complex Systems
  • Instructor, Big Dive Data Science Program (2012–2020): Integrating academic and industry participants in practical machine learning and visualization
Doctoral Supervision
  • Simone Piaggesi — Graph Learning (University of Bologna)
  • Arianna Miola — Explainable AI (University of Milano-Bicocca)
  • Co-supervision of multiple theses on fairness and interpretability
Graduate Mentoring
  • Supervised MSc research on fairness, graph explainability, synthetic data, and agent-based modeling

Community & Service

Leadership & Editorial
  • President, Scientific Advisory Board — Anti-Financial Crime Digital Hub
  • Guest Editor, EPJ Data Science
Conference Organization
  • Chair, KDD Cup 2024
  • Area Chair, The WebConf 2024
  • Special Event Chair, AI for Financial Crime Fight (ECML PKDD 2023)
  • Track Chair, Applied Explainable AI (AMLD 2024)
Funding & Consortia
  • EU Horizon Projects: Principal Investigator (PRE-ACT) and Partner (CEDAR) on fairness, transparency, and governance-ready AI; leadership in Horizon 2020/Europe programmes
  • Industry Partnerships: Directed multi-year collaborations with Intesa Sanpaolo (legal litigation risk estimation, GenAI for passive guarantees analysis, churn prediction) and AFC-DH (explainability platforms, synthetic data evaluation, payment filtering)
Academic Review
  • Reviewer and PC member for NeurIPS, ICLR, KDD, WWW, xAI, and TMLR

Contact

Location
Turin, Italy
Email
panisson [at] gmail [dot] com
Web
andre.panisson.com